Indexing Patterns in Graph Databases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10380577" target="_blank" >RIV/00216208:11320/18:10380577 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21240/18:00326756

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0006826903130321" target="_blank" >http://dx.doi.org/10.5220/0006826903130321</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0006826903130321" target="_blank" >10.5220/0006826903130321</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Indexing Patterns in Graph Databases

Popis výsledku v původním jazyce

Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, graph-based bibliographic IR, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional IS based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is organized in a tree structure and stored in the same database where the database graph. The method is analysed and implemented for Neo4j GDB engine. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides a comparison between queries with and without using indexes.

Název v anglickém jazyce

Indexing Patterns in Graph Databases

Popis výsledku anglicky

Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, graph-based bibliographic IR, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional IS based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is organized in a tree structure and stored in the same database where the database graph. The method is analysed and implemented for Neo4j GDB engine. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides a comparison between queries with and without using indexes.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA

ISBN

978-989-758-318-6

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

9

Strana od-do

313-321

Název nakladatele

SciTePress

Místo vydání

Setúbal

Místo konání akce

Porto

Datum konání akce

26. 7. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—